Strong-Help-Weak: An Online Multi-Task Inference Learning Approach for Robust Advanced Driver Assistance Systems
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2024.3430811
Abstract: Multi-task learning in advanced driver assistance systems aims to endow models with the capacity to jointly handle multiple related tasks, such as object detection, depth estimation, and more. However, existing multi-task learning models largely rely… read more here.
Keywords: task; lane line; multi task; inference learning ... See more keywords
An Application of Random Walk Resampling to Phylogenetic HMM Inference and Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on NanoBioscience"
DOI: 10.1109/tnb.2020.2991302
Abstract: Statistical resampling methods are widely used for confidence interval placement and as a data perturbation technique for statistical inference and learning. An important assumption of popular resampling methods such as the standard bootstrap is that… read more here.
Keywords: application random; inference; sequence; inference learning ... See more keywords
Deep-Variational-Inference-Learning Detection for Cell-Free Massive MIMO With Quantization Error
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2025.3534820
Abstract: A deep variational inference learning (DVIL) framework is proposed for data detection for cell-free massive multiple-input multiple-output (MIMO). The unknown model of the superimposed noise of quantization error and the environment noise is extracted based… read more here.
Keywords: variational inference; cell free; inference learning; deep variational ... See more keywords
Neural spiking for causal inference and learning
Sign Up to like & getrecommendations! Published in 2023 at "PLOS Computational Biology"
DOI: 10.1371/journal.pcbi.1011005
Abstract: When a neuron is driven beyond its threshold, it spikes. The fact that it does not communicate its continuous membrane potential is usually seen as a computational liability. Here we show that this spiking mechanism… read more here.
Keywords: causal inference; neural spiking; inference learning; causal ... See more keywords